Extrudate swell and flow analysis of polystyrene melt flowing in an electro‐magnetized die in a single screw extruder

An electro‐magnetized capillary die via a parallel co‐extrusion technique was used to study the changes in the overall and radial extrudate swell ratio of polystyrene (PS) melt flowing in a single screw extruder. The effects of magnetic flux density, wall shear rate (screw rotating speed) and die temperature were studied. The results suggested that, in the case of non‐magnetic die the average overall swell ratio of the melt ranged from 1.25 to 1.55. The swelling ratio increased with increasing wall shear rate up to 8.5 sec^?1 and then decreased at 17.1 sec^?1. Increasing die temperature caused a reduction of extrudate swell ratio. The changes in extrudate swell ratio can be explained using the simultaneously measured velocity profiles during the flow in the die, and the swell ratio decreased with increasing radial position. Melt contraction of the melt layer near the die wall was observed. The die temperature was found to have no effect on the change of the radial extrudate swell profiles. When an electro‐magnetized die was used, the average overall swell ratio was found to increase with increasing magnetic flux density to a maximum value and then decreased at higher flux densities. The magnetic flux density of the maximum swell was changed by the wall shear rate. It was associated with a balance of elastic and magnetic energies during the flow. The magnetic energy was thought to have a pronounced effect on the swell ratio at low shear rate and low die temperature. Considering the radial position, the highest swell ratio occurred at the duct center, in the range 2.4–3.3. There was no extrudate contraction of the melt layer near the die wall. Copyright © 2005 John Wiley & Sons, Ltd.     

基于分子对接的苯丙素甙（PPGs）类化合物的虚拟筛选和合理设计

采用虚拟化合物生成法对抗肿瘤的苯丙素甙(PPGs)类化合物进行了配体受体对 接研究。以三种不同的骨架结构为基础分别生成了五十个虚拟苯丙素甙(PPGs)类化 合物，并将它们与端粒DNA受体进行分子对接，分析已知结构的对接结果，通过虚 拟筛选的方法得到了一批与受体相互作用能较高并且复合物能量较低的新的有潜力 的活性化合物。该方法可以弥补分子对接研究中，只能计算药物与受体的相互作用 ，无法有效设计新化合物的不足。这种方法在基于结构的药物分子设计中具有重要 的意义。     

Mechanisms behind concentration profiles illustrated by charge and concentration distributions around ions in double layers

The mechanisms behind the behaviour of concentration and charge density profiles in diffuse electric double layers are investigated quantitatively for 1:1 and 2:2 electrolytes. This is done by analysing various contributions to the mean force that acts on each ion. The forces are obtained from the calculated ionic charge and concentration distributions around individual ions at various positions in the double layer. These distributions are presented graphically which allows an immediate visual illustration of the mechanisms in action. Some features studied are charge inversion in double layers for divalent aqueous electrolytes, overcompensation of surface charge due to large amounts of physisorbed counterions, ion size effects in the double layer structure and various mechanisms that cause deviations from the predictions of the Poisson–Boltzmann approximation. A major objective of the paper is to present the results in a visual form and explain aspects of modern double layer theory in a simple manner.     

Water‐Soluble Molecular Capsules: Self‐Assembly and Binding Properties

The self‐assembly and characterization of water‐soluble calix[4]arene‐based molecular capsules ( 1?2 ) is reported. The assemblies are the result of ionic interactions between negatively charged calix[4]arenes 1 a and 1 b , functionalized at the upper rim with amino acid moieties, and a positively charged tetraamidiniumcalix[4]arene 2 . The formation of the molecular capsules is studied by ¹H NMR spectroscopy, ESI mass spectrometry (ESI‐MS), and isothermal titration calorimetry (ITC). A molecular docking protocol was used to identify potential guest molecules for the self‐assembled capsule 1 a?2 . Experimental guest encapsulation studies indicate that capsule 1 a?2 is an effective host for both charged (N‐methylquinuclidinium cation) and neutral molecules (6‐amino‐2‐methylquinoline) in water.     

Interactions of peptide mimics of hyaluronic acid with the receptor for hyaluronan mediated motility (RHAMM)

Summary Using the hyaluronic acid (HA) binding region of the receptor for hyaluronan-mediated motility (RHAMM) as a model, a molecular perspective for peptide mimicry of the natural ligand was established by comparing the interaction sites of HA and unnatural peptide–ligands to RHAMM. This was accomplished by obtaining a series of octapeptide–ligands through screening experiments that bound to the HA binding domains of RHAMM (amino acids 517–576) and could be displaced by HA. These molecules were computationally docked onto a three-dimensional NMR based model of RHAMM. The NMR model showed that RHAMM(517–576) was a set of three helices, two of which contained the HA binding domains (HABDs) flanking a central groove. The structure was stabilized by hydrophobic interactions from four pairs of Val and Ile side chains extending into the groove. The presence of solvent exposed, positively charged side chains spaced 11Å apart matched the spacing of negative charges on HA. Docking experiments using flexible natural and artificial ligands demonstrated that HA and peptide–mimetics preferentially bound to the second helix that contains HABD-2. Three salt bridges between HA carboxylates and Lys548, Lys553 and Lys560 and two hydrophobic interactions involving Val538 and Val559 were predicted to stabilize the RHAMM-HA complex. The high affinity peptides and HA utilized the same charged residues, with additional contacts to other basic residues. However, hydrophobic contacts do not contribute to affinity for peptide ligand-RHAMM complexes. These results offer insight into how selectivity is achieved in the binding of HA to RHAMM, and how peptide competitors may compete for binding with HA on a single hyaladherin.     

Selectivity analysis of 5-(arylthio)-2,4-diaminoquinazolines as inhibitors of Candida albicans dihydrofolate reductase by molecular dynamics simulations

A series of 5-(arylthio)-2,4-diaminoquinazolines are known as selective inhibitors of dihydrofolate reductase (DHFR) from Candida albicans. We have performed docking and molecular dynamics simulations of these inhibitors with C. albicans and human DHFR to understand the basis for selectivity of these agents. Study was performed on a selected set of 10 compounds with variation in structure and activity. Molecular dynamics simulations were performed at 300 K for 45 ps with equilibration for 10 ps. Trajectory data was analyzed on the basis of hydrogen bond interactions, energy of binding and conformational energy difference. The results indicate that hydrogen bonds formed between the compound and the active site residues are responsible for inhibition and higher potency. The selectivity index, i.e the ratio of I₅₀ against human DHFR to I₅₀ against fungal DHFR, is mainly determined by the conformation adapted by the compounds within the active site of two enzymes. Since the human DHFR active site is rigid, the compound is trapped in a higher energy conformation. This energy difference between the two conformations E mainly governs the selectivity against fungal DHFR. The information generated from this analysis of potency and selectivity should be useful for further work in the area of antifungal research.     

Predicting sequences and structures of MHC-binding peptides: a computational combinatorial approach

Peptides bound to MHC molecules on the surface of cells convey critical information about the cellular milieu to immune system T cells. Predicting which peptides can bind an MHC molecule, and understanding their modes of binding, are important in order to design better diagnostic and therapeutic agents for infectious and autoimmune diseases. Due to the difficulty of obtaining sufficient experimental binding data for each human MHC molecule, computational modeling of MHC peptide-binding properties is necessary. This paper describes a computational combinatorial design approach to the prediction of peptides that bind an MHC molecule of known X-ray crystallographic or NMR-determined structure. The procedure uses chemical fragments as models for amino acid residues and produces a set of sequences for peptides predicted to bind in the MHC peptide-binding groove. The probabilities for specific amino acids occurring at each position of the peptide are calculated based on these sequences, and these probabilities show a good agreement with amino acid distributions derived from a MHC-binding peptide database. The method also enables prediction of the three-dimensional structure of MHC-peptide complexes. Docking, linking, and optimization procedures were performed with the XPLOR program [1].     

Existence and asymptotic behavior to the incompressible nematic liquid crystal flow in the whole space

In this article, first of all, the global existence and asymptotic stability of solutions to the incompressible nematic liquid crystal flow is investigated when initial data are a small perturbation near the constant steady state (0,δ₀); here, δ₀ is a constant vector with |δ₀|=1. Precisely, we show the existence and asymptotic stability with small initial data for . The initial data class of us is not entirely included in the space BMO^?1×BMO and contains strongly singular functions and measures. As an application, we obtain a class of asymptotic existence of a basin of attraction for each self‐similar solution with homogeneous initial data. We also study global existence of a large class of decaying solutions and construct an explicit asymptotic formula for ∣x∣→∞, relating the self‐similar profile (U(x),D(x)) to its corresponding initial data (u₀,d₀). In two dimensions, we obtain higher‐order asymptotics of (u(x),d(x)). Copyright © 2016 John Wiley & Sons, Ltd.     

Investigation on the isoform selectivity of novel kinesin-like protein 1 (KIF11) inhibitor using chemical feature based pharmacophore,molecular docking,and quantum mechanical studies

Kinesin-like protein (KIF11) is a molecular motor protein that is essential in mitosis. Removal of KIF11 prevents centrosome migration and causes cell arrest in mitosis. KIF11 defects are linked to the disease of microcephaly, lymph edema or mental retardation. The human KIF11 protein has been actively studied for its role in mitosis and its potential as a therapeutic target for cancer treatment. Pharmacophore modeling, molecular docking and density functional theory approaches was employed to reveal the structural, chemical and electronic features essential for the development of small molecule inhibitor for KIF11. Hence we have developed chemical feature based pharmacophore models using Discovery Studio v 2.5 (DS). The best hypothesis (Hypo1) consisting of four chemical features (two hydrogen bond acceptor, one hydrophobic and one ring aromatic) has exhibited high correlation co-efficient of 0.9521, cost difference of 70.63 and low RMS value of 0.9475. This Hypo1 is cross validated by Cat Scramble method; test set and decoy set to prove its robustness, statistical significance and predictability respectively. The well validated Hypo1 was used as 3Dquery to perform virtual screening. The hits obtained from the virtual screening were subjected to various scrupulous drug-like filters such as Lipinski’s rule of five and ADMET properties. Finally, six hit compounds were identified based on the molecular interaction and its electronic properties. Our final lead compound could serve as a powerful tool for the discovery of potent inhibitor as KIF11 agonists.